Noted a remarkable 5% improvement in specific power consumption, India's leading Aluminum Manufacturer has achieved a landmark by optimizing Aluminum smelting potlines.

The current software solutions fall short in meeting Key Result Area (KRA) targets, compelling the need for an enhanced approach. Particularly, in situations where operators must exercise judgment regarding AlF3 feed values, existing systems prove inadequate. With only 40% of potline baths currently operate at an optimal temperature, and a concerning 70% of the time witnesses’ instances of over-steer or under-steer. Given that power consumption constitutes over 80% of the associated costs, it becomes imperative to address the crucial factor of maintaining optimal bath temperature.

Additionally, the need for time-consuming Root Cause Analysis (RCA) further compounds the complexity of addressing and rectifying issues in the manufacturing process. To address these critical issues, there is a clear demand for reliable and high-performance recommender systems specifically tailored for key variables, such as AlF3. The software should alleviate the dependence on human judgment, mitigate deviations, and streamline the analysis of root causes for a more resource-efficient manufacturing process.